Geological controls on grade by size fractionation in gold systems

The Cooperative Research Centre for Optimising Resource Extraction (CRC ORE) has developed a methodology called Grade Engineering® (GE) that aims to improve effective feed grades of large, low grade mining operations. GE involves using a range of integrated technologies and operating protocols to facilitate early rejection of low value material. Preferential grade by size fractionation is a foundation of GE and is based on the natural tendency of some mineral phases to preferentially fractionate during breakage into different size fractions (Walters, 2016; Rutter, 2017). Carrasco (2013) and Carrasco et al. (2016) developed a mathematical model to describe preferential grade by size fractionation through a Response Ranking (RR) factor that ranges from 0 to 200. When the RR values in drill core samples are >80, the material shows high potential for upgrade via screening using GE methodology. RR values from 20 to 80 indicate that the material needs integration of an additional lever in the GE suite, such as differential blasting and screening. RR values <20 mean that the material will not be a significant driver for GE (CRC ORE, 2014). In some cases, there are negative RR values that indicates metal is deporting to the coarse fraction (Dyer, 2019). The geological controls on grade by size fractionation and associated RR values vary between ore bodies and mineralisation types. Therefore, detailed evaluation is required on a case by case basis to assess a deposits potential for grade by size fractionation.

This project aims to evaluate and understand the geological controls on grade by size fractionation and the RR parameter using drill core from two intrusion-related gold systems (Gramalote and Telfer deposits) and bulk samples from one of the deposits (Gramalote). Detailed logging of rock samples and mineralogical analyses including hyperspectral logging, portable and bench-scale X-Ray Fluorescence (XRF), plus low-resolution Laser Ablation ICP-MS (Inductively Coupled Plasma Mass Spectrometer) analyses in intact drill core pieces, combined with data from site (drill logs, geochemistry, petrophysics) were used to evaluate ore and alteration mineralogy, vein paragenesis and textural variability. These data provided information on gold deportment and allowed the identification of favourable host materials for grade by size fractionation. A comparison of geological parameters with the results of GE testing showed that samples with RR Au >80 present high hardness and have abundant numbers of mineralised veins, but a low amount of vein material. Samples with RR Au 80–20 gave varied responses due to the different types of mineralized veins. For example, at Gramalote, drill core intervals in the RR 80-20 group have a high number of mineralised veins in stockworks or a high number of poorly-mineralised veins; while samples from the Telfer deposit in the RR Au 80–20 class present high percentages of mineralised veins. In both deposits the RR Au 20–0 class is characterised by low amounts of mineralised veins.The RR Au negative class is related to thicker mineralised veins.

Analyses of data, in combination with machine learning, allowed an estimation of RR classes. Through the analysis of RR classes in conjunction with data collected via a combination of automated systems including hyperspectral data and XRF, plus detailed drill core logging, this work indicates that an upgrade response can be predicted from drill core samples. In addition, this work contributes to further understanding of the influence of mineralogy and rock textures on rock breakage and natural fractionation.